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Journal articles on the topic 'Numerical mathematics'

Author: Grafiati

Published: 4 June 2021

Last updated: 26 January 2023

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1

Iserles, A., G. Hammerlin, and K. H. Hoffmann. "Numerical Mathematics." Mathematical Gazette 78, no. 481 (1994): 91. http://dx.doi.org/10.2307/3619466.

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2

G., W., Gunther Hammerlin, Karl-Heinz Hoffmann, and Larry Schumaker. "Numerical Mathematics." Mathematics of Computation 58, no. 198 (1992): 855. http://dx.doi.org/10.2307/2153223.

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3

I., E., Heinz Rutishauser, and Walter Gautschi. "Lectures on Numerical Mathematics." Mathematics of Computation 57, no. 196 (1991): 869. http://dx.doi.org/10.2307/2938724.

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4

Brezinski, Claude. "Lectures on Numerical mathematics." Numerical Algorithms 1, no. 1 (1991): 117. http://dx.doi.org/10.1007/bf02145584.

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5

Benner, Peter, Daniel Kressner, and Hoang Xuan Phu. "Numerical Mathematics and Control." Vietnam Journal of Mathematics 48, no. 4 (2020): 615–20. http://dx.doi.org/10.1007/s10013-020-00451-x.

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6

Temme, Nico M. "Numerical aspects of special functions." Acta Numerica 16 (April 24, 2007): 379–478. http://dx.doi.org/10.1017/s0962492906330012.

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This paper describes methods that are important for the numerical evaluation of certain functions that frequently occur in applied mathematics, physics and mathematical statistics. This includes what we consider to be the basic methods, such as recurrence relations, series expansions (both convergent and asymptotic), and numerical quadrature. Several other methods are available and some of these will be discussed in less detail. Examples will be given on the use of special functions in certain problems from mathematical physics and mathematical statistics (integrals and series with special fun

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7

Kathleen Heid, M. "How Symbolic Mathematical Systems Could and Should Affect Precollege Mathematics." Mathematics Teacher 82, no. 6 (1989): 410–19. http://dx.doi.org/10.5951/mt.82.6.0410.

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Computer programs are now available that perform most of the algebraic and numerical-manipulation procedures on which school mathematics now concentrates. The defining characteristic of these symbolic mathematical systems is that, unlike many of the popular computer languages, they can manipulate variables as well as numbers. They can perform rationalnumber arithmetic, solve equations, produce equivalent expressions of a variety of types, apply trigonometric identities, evaluate limits and sums, compute the algebraic form of derivatives and integrals, perform matrix manipulations, and produce

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8

Croft, A., and Elizabeth West. "Numerical Analysis, (MEI Structured Mathematics)." Mathematical Gazette 79, no. 484 (1995): 180. http://dx.doi.org/10.2307/3620058.

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9

Albers, Don. "John Todd—Numerical Mathematics Pioneer." College Mathematics Journal 38, no. 1 (2007): 2–23. http://dx.doi.org/10.1080/07468342.2007.11922213.

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10

Klepikov, P. N. "Mathematical Modeling in Problems of Homogeneous (Pseudo)Riemaimian Geometry." Izvestiya of Altai State University, no. 1(111) (March 6, 2020): 95–98. http://dx.doi.org/10.14258/izvasu(2020)1-15.

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Currently, mathematical and computer modeling, as well as systems of symbolic calculations, are actively used in many areas of mathematics. Popular computer math systems as Maple, Mathematica, MathCad, MatLab allow not only to perform calculations using symbolic expressions but also solve algebraic and differential equations (numerically and analytically) and visualize the results. Differential geometry, like other areas of modern mathematics, uses new computer technologies to solve its own problems. The applying is not limited only to numerical calculations; more and more often, computer math

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11

Kahaner, David K., and Carl-Erik Froberg. "Numerical Mathematics--Theory and Computer Applications." Mathematics of Computation 48, no. 178 (1987): 829. http://dx.doi.org/10.2307/2007845.

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12

I., E., David Kincaid, and Ward Cheney. "Numerical Analysis--Mathematics of Scientific Computing." Mathematics of Computation 59, no. 199 (1992): 297. http://dx.doi.org/10.2307/2152998.

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13

Bright, George W. "Teaching Mathematics with Technology: Numerical Relationships." Arithmetic Teacher 36, no. 6 (1989): 56–58. http://dx.doi.org/10.5951/at.36.6.0056.

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Numerical relationships are very important in mathematics, yet students frequently have difficulty dealing with them. For example, as the denominator of a positive fraction increases, the value of the fraction decreases, but students many times still want to order fractions incorrectly according to the size of the denominators. Calculators furnish some of the needed mind-expanding support that students need to investigate the value of fractions as the numerators or denominators change.

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14

Laamena, Christina Martha, and Toto Nusantara. "Prospective mathematics teachers’ argumentation structure when constructing a mathematical proof: The importance of backing." Beta: Jurnal Tadris Matematika 12, no. 1 (2019): 43–59. http://dx.doi.org/10.20414/betajtm.v12i1.272.

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 [English]: This qualitative study with phenomenology design aims to investigate the use of backing and its relation to rebuttal and qualifier in prospective mathematics teachers’ (PMTs) argumentation when constructing a mathematical proof about algebraic function. The data were collected through subjects' works on the proof, recorded think-aloud data, and in-depth interviews. Data analysis was guided by Toulmin’s argumentation scheme. The results show that the PMTs used three types of backing, i.e., backing in the form of definitions or theorems (reference backing), examples of numbers

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15

Suggate, Sebastian, Heidrun Stoeger, and Ursula Fischer. "Finger-Based Numerical Skills Link Fine Motor Skills to Numerical Development in Preschoolers." Perceptual and Motor Skills 124, no. 6 (2017): 1085–106. http://dx.doi.org/10.1177/0031512517727405.

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Previous studies investigating the association between fine-motor skills (FMS) and mathematical skills have lacked specificity. In this study, we test whether an FMS link to numerical skills is due to the involvement of finger representations in early mathematics. We gave 81 pre-schoolers (mean age of 4 years, 9 months) a set of FMS measures and numerical tasks with and without a specific finger focus. Additionally, we used receptive vocabulary and chronological age as control measures. FMS linked more closely to finger-based than to nonfinger-based numerical skills even after accounting for t

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16

Randall, T. J., and R. E. Scraton. "BASIC Numerical Methods (An Introduction to Numerical Mathematics on a Microcomputer)." Mathematical Gazette 69, no. 450 (1985): 317. http://dx.doi.org/10.2307/3617608.

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17

Lyashenko, Viktor, Elena Kobilskaya, and Tetiana Nabok. "APPLICATION OF MATHEMATICS SOFTWARE FOR SOLVING APPLIED PROBLEMS." Transactions of Kremenchuk Mykhailo Ostrohradskyi National University, no. 3(128) (June 11, 2021): 11–16. http://dx.doi.org/10.30929/1995-0519.2021.3.11-16.

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Purpose. To show the possibilities of using mathematics software in solving problems arising in the construction of mathematical models of various processes and, thus, to reveal the importance of realizing the professional orientation of the mathematical training of students of natural and engineering specialties. Methodology. A number of mathematical models that are presented in the form of a Cauchy problem for a common first-order differential equation are considered in this paper. Mathematical models considered in this paper describe chemical and ecological processes. Euler's numerical meth

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18

Moustafa, Ahmed A., Richard Tindle, Zaheda Ansari, Margery J. Doyle, Doaa H. Hewedi, and Abeer Eissa. "Mathematics, anxiety, and the brain." Reviews in the Neurosciences 28, no. 4 (2017): 417–29. http://dx.doi.org/10.1515/revneuro-2016-0065.

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AbstractGiven that achievement in learning mathematics at school correlates with work and social achievements, it is important to understand the cognitive processes underlying abilities to learn mathematics efficiently as well as reasons underlying the occurrence of mathematics anxiety (i.e. feelings of tension and fear upon facing mathematical problems or numbers) among certain individuals. Over the last two decades, many studies have shown that learning mathematical and numerical concepts relies on many cognitive processes, including working memory, spatial skills, and linguistic abilities.

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19

ISHIKAWA, Hideaki. "Highly Accurate, Numerical Method for Calculating Mathematical Functions Defined by Integrals: Feedback from Numerical Analysis for Quantum Mechanics to Mathematics and Numerical Analysis." Journal of Computer Chemistry, Japan 14, no. 3 (2015): 47–49. http://dx.doi.org/10.2477/jccj.2015-0038.

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20

Herceg, Dragoslav, and Đorđe Herceg. "Numerical mathematics with GeoGebra in high school." Teaching Mathematics and Computer Science 6, no. 2 (2008): 363–78. http://dx.doi.org/10.5485/tmcs.2008.0185.

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21

Planitz, Max, and T. R. F. Nonweiler. "Computational Mathematics: An Introduction to Numerical Approximation." Mathematical Gazette 69, no. 447 (1985): 67. http://dx.doi.org/10.2307/3616478.

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22

Eko, Fitrianto, Yohanes Leonardus, Wardono Wardono, and Isnaini Rosyida. "Mathematics Pre-Service Teachers’ Numerical Thinking Profiles." European Journal of Educational Research 11, no. 2 (2022): 1075–87. http://dx.doi.org/10.12973/eu-jer.11.2.1075.

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<p style="text-align: justify;">Numerical thinking is needed to recognize, interpret, determine patterns, and solve problems that contain the context of life. Self-efficacy is one aspect that supports the numerical thinking process. This study aims to obtain a numerical thinking profile of Mathematics pre-service teachers based on self-efficacy. This study used descriptive qualitative method. The data obtained were based on the results of questionnaires, tests, and interviews. The results of the self-efficacy questionnaire were analyzed and categorized (high, moderate, and low). Two info

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23

Jacques, I. B., and C. J. Judd. "Use of microcomputers in teaching numerical mathematics." International Journal of Mathematical Education in Science and Technology 16, no. 3 (1985): 347–54. http://dx.doi.org/10.1080/0020739850160303.

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24

Butcher, J. C. "Initial value problems: numerical methods and mathematics." Computers & Mathematics with Applications 28, no. 10-12 (1994): 1–16. http://dx.doi.org/10.1016/0898-1221(94)00182-0.

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25

Wimp, Jet, and T. R. F. Nonweiler. "Computational Mathematics, An Introduction to Numerical Approximation." Mathematics of Computation 46, no. 174 (1986): 761. http://dx.doi.org/10.2307/2008016.

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26

Jeong, Young-Sik, Mohammad S. Obaidat, Jianhua Ma, and Laurence T. Yang. "Advanced Mathematics and Numerical Modeling of IoT." Journal of Applied Mathematics 2015 (2015): 1–5. http://dx.doi.org/10.1155/2015/824891.

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27

Rips, Lance J., Amber Bloomfield, and Jennifer Asmuth. "From numerical concepts to concepts of number." Behavioral and Brain Sciences 31, no. 6 (2008): 623–42. http://dx.doi.org/10.1017/s0140525x08005566.

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AbstractMany experiments with infants suggest that they possess quantitative abilities, and many experimentalists believe that these abilities set the stage for later mathematics: natural numbers and arithmetic. However, the connection between these early and later skills is far from obvious. We evaluate two possible routes to mathematics and argue that neither is sufficient: (1) We first sketch what we think is the most likely model for infant abilities in this domain, and we examine proposals for extrapolating the natural number concept from these beginnings. Proposals for arriving at natura

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28

Wei, Hui Xian. "Application of Method of Undetermined Coefficients in the Higher Mathematics." Advanced Materials Research 926-930 (May 2014): 3489–92. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.3489.

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Method of undetermined coefficients as a method of solving mathematical problems in Higher Mathematics a wide range of applications, this method of undetermined coefficients in Mathematical Analysis, Numerical Methods, differential equations, some applications of the analytic geometry of four courses made a brief, and gives examples.

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29

Anindita Roy Chowdhury and Naresh Sharma. "Scientific Numerical Pattern in Stringed-Fretted Musical Instrument." Mathematical Journal of Interdisciplinary Sciences 8, no. 2 (2020): 69–74. http://dx.doi.org/10.15415/mjis.2020.82009.

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Music, a creative art has a strong foundation on science and mathematics. Source of music can vary from vocal chord to various types of musical instruments. One of the popular stringed and fretted musical instrument, the guitar has been discussed here. The structure of the guitar is based on mathematical and scientific concepts. Harmonics and frequency play pivotal role in generation of music from a guitar. In this paper, the authors have investigated various factors related to the structure of a guitar. Aspects related to the musical notes of a guitar have been analyzed to gain a better insig

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30

Bultheel, A. "Numerical methods." Journal of Computational and Applied Mathematics 24, no. 3 (1988): N2. http://dx.doi.org/10.1016/0377-0427(88)90305-6.

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31

Lavrischeva, Ekaterina Mikhailovna, and Igor Borisovich Petrov. "Modeling Technical and Mathematical Tasks of Applied Knowledge Areas on Computers." Proceedings of the Institute for System Programming of the RAS 32, no. 6 (2020): 167–82. http://dx.doi.org/10.15514/ispras-2020-32(6)-13.

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The paper considers modeling of technical problems and problems of applied mathematics, their algorithms and programming. The characteristics of the numerical modeling of technical problems and applied mathematics are given: physical and technical experiments, energy, ballistic and seismic methods of I.V. Kurchatov, starting with mathematical methods of the 17-20th centuries, the first computers and computers. The analysis of the first technical problems and problems of applied mathematics, their modeling, algorithmization and programming using the A.A. Lyapunov graph-schematic language, addre

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32

Kulabukhov, S. Yu. "Mathematical modeling in informatiсs lessons using numerical solution of differential equations". Informatics in school, № 2 (27 квітня 2021): 14–21. http://dx.doi.org/10.32517/2221-1993-2021-20-2-14-21.

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The article considers the author's fragment of an in-depth course of informatics in a physics and mathematics school. It is based on the use of differential equations to model complex physical processes. Three models are considered: a mathematical spring pendulum, the orbital motion of the satellite around the planet and the movement of the body in the atmosphere taking into account air resistance. Since in the in-depth course of mathematics of the physics and mathematics school, numerical methods for solving differential equations are not studied, the article proposes to use the simplest meth

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33

Kissane, Barry. "The Scientific Calculator and School Mathematics." Southeast Asian Mathematics Education Journal 6, no. 1 (2016): 29–48. http://dx.doi.org/10.46517/seamej.v6i1.38.

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Scientific calculators are sometimes regarded as important only for obtaining numerical answers to computational questions, and thus in some countries regarded as inappropriate for school mathematics, lest they might undermine the school curriculum. This paper argues a contrary view that, firstly, numerical computation is not the principal purpose of scientific calculators in education, and secondly that calculators can play a valuable role in supporting students’ learning. Recent developments of calculators are outlined, noting that theirprincipal intention has been to make calculators easier

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34

Chen, Chin Chun. "Construct Concept Structure for Fundamental Mathematics." Applied Mechanics and Materials 145 (December 2011): 436–40. http://dx.doi.org/10.4028/www.scientific.net/amm.145.436.

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Currently, cognitive psychologists and mathematics educators are looking again at conceptual and procedural knowledge in mathematics learning. Building relationship between conceptual knowledge and the procedures of mathematics contributes to long-term memory of procedures and to their effective use. So we know that symbols could enhance concept and procedures apply concepts to solve problem efficiently. Sketch the graph of exponential function and logarithmic function. Find the inverse exponential function, logarithmic function and so on. The lack of other concrete example in general exponent

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35

Seng, Ernest Lim Kok. "The Influence of Pre-University Students’ Mathematics Test Anxiety and Numerical Anxiety on Mathematics Achievement." International Education Studies 8, no. 11 (2015): 162. http://dx.doi.org/10.5539/ies.v8n11p162.

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<p class="apa">This study examines the relationship between mathematics test anxiety and numerical anxiety on students’ mathematics achievement. 140 pre-university students who studied at one of the institutes of higher learning were being investigated. Gender issue pertaining to mathematics anxieties was being addressed besides investigating the magnitude of the variables for mathematics test anxiety and numerical anxiety. The data revealed that there was a positive correlation between mathematics test anxiety and numerical anxiety on students’ mathematics achievement. Results of the mu

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36

BRUZZO, UGO, and BEATRIZ GRAÑA OTERO. "NUMERICALLY FLAT HIGGS VECTOR BUNDLES." Communications in Contemporary Mathematics 09, no. 04 (2007): 437–46. http://dx.doi.org/10.1142/s0219199707002526.

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After providing a suitable definition of numerical effectiveness for Higgs bundles, and a related notion of numerical flatness, in this paper we prove, together with some side results, that all Chern classes of a Higgs-numerically flat Higgs bundle vanish, and that a Higgs bundle is Higgs-numerically flat if and only if it is has a filtration whose quotients are flat stable Higgs bundles. We also study the relation between these numerical properties of Higgs bundles and (semi)stability.

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37

Arthur, D. W., D. Greenspan, and V. Casulli. "Numerical Analysis for Applied Mathematics, Science and Engineering." Mathematical Gazette 73, no. 466 (1989): 354. http://dx.doi.org/10.2307/3619336.

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38

Sasanguie, Delphine, Bert De Smedt, Emmy Defever, and Bert Reynvoet. "Association between basic numerical abilities and mathematics achievement." British Journal of Developmental Psychology 30, no. 2 (2011): 344–57. http://dx.doi.org/10.1111/j.2044-835x.2011.02048.x.

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39

Dejic, Mirko. "Position and role of numerical mathematics in teaching." Godisnjak Pedagoskog fakulteta u Vranju, no. 7 (2016): 347–61. http://dx.doi.org/10.5937/gufv1607347d.

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40

Ziegel, Eric R. "Numerical Methods for Computer Science, Engineering, and Mathematics." Technometrics 30, no. 2 (1988): 245. http://dx.doi.org/10.1080/00401706.1988.10488396.

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41

Ames, W. F. "Numerical analysis for applied mathematics, science and engineering." Mathematics and Computers in Simulation 30, no. 4 (1988): 373. http://dx.doi.org/10.1016/s0378-4754(98)90011-8.

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42

Wanga, Herbert, Stephano Sanga, Shangweli Kituma, Thobius Joseph, and Rose Mzilangwe. "Computer Scientists: Why Numerical Instead of Analytical Mathematics?." International Journal of Computer Science and Mobile Computing 9, no. 10 (2020): 112–16. http://dx.doi.org/10.47760/ijcsmc.2020.v09i10.014.

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43

Willoughby, Ralph A. "Numerical Mathematics (Günther Hämmerline and Karl-Heinz Hoffman)." SIAM Review 35, no. 1 (1993): 174–75. http://dx.doi.org/10.1137/1035041.

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44

Bernard, Bernard, Ahmad Talib, and Megawati Megawati. "The Effect of Self-Potential, Study Habits, and Numerical Abilities on The Mathematics Learning Outcomes of Junior High School Students." SAINSMAT: Journal of Applied Sciences, Mathematics, and Its Education 11, no. 2 (2022): 81–89. http://dx.doi.org/10.35877/sainsmat195.

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This study is a quantitative study with an ex post facto approach aimed at knowing the effect of self-potential, study habits and numerical abilities on the mathematics learning outcomes of junior high school students. The sample in this study was 78 students of SMP class VIII who were selected using simple random sampling technique. The data collection technique used in this research is the test and questionnaire method. The instruments used are self-potential questionnaires, study habits questionnaires, numerical ability tests and mathematics learning outcomes tests. The data analysis techni

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45

Soylu, Firat, Frank K. Lester, and Sharlene D. Newman. "You can count on your fingers: The role of fingers in early mathematical development." Journal of Numerical Cognition 4, no. 1 (2018): 107–35. http://dx.doi.org/10.5964/jnc.v4i1.85.

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Even though mathematics is considered one of the most abstract domains of human cognition, recent work on embodiment of mathematics has shown that we make sense of mathematical concepts by using insights and skills acquired through bodily activity. Fingers play a significant role in many of these bodily interactions. Finger-based interactions provide the preliminary access to foundational mathematical constructs, such as one-to-one correspondence and whole-part relations in early development. In addition, children across cultures use their fingers to count and do simple arithmetic. There is al

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46

Matušů, Josef, Gejza Dohnal, and Martin Matušů. "On one method of numerical integration." Applications of Mathematics 36, no. 4 (1991): 241–63. http://dx.doi.org/10.21136/am.1991.104464.

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47

Botta, Nicola, and Rolf Jeltsch. "A numerical method for unsteady flows." Applications of Mathematics 40, no. 3 (1995): 175–201. http://dx.doi.org/10.21136/am.1995.134290.

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48

López-Reyes, Luis Javier. "Collaborative learning of differential equations by numerical simulation." World Journal on Educational Technology: Current Issues 14, no. 1 (2022): 56–63. http://dx.doi.org/10.18844/wjet.v14i1.6637.

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This paper presents a didactic proposal designed through the active methodology of Collaborative Learning to analyse the effect of the use of numerical simulation of a mathematical model on the learning of differential equations in engineering students. A mathematical model of a vibrating string was used, and the Octave Online platform was used for the numerical simulation. The analysis and assessment of this proposal was carried out in a hybrid, quantitative and qualitative manner, through the design of observation and measurement instruments. The results indicate that in STEM programs, the u

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49

Halme, Hilma, Kelly Trezise, Minna M. Hannula-Sormunen, and Jake McMullen. "Characterizing mathematics anxiety and its relation to performance in routine and adaptive tasks." Journal of Numerical Cognition 8, no. 3 (2022): 414–29. http://dx.doi.org/10.5964/jnc.7675.

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Mathematics anxiety hinders students' mathematical achievement already in primary school, but research on its effects beyond whole number knowledge is limited. The main aim of the current study is to examine how state and trait mathematics anxiety relate to performance across five tasks that are relevant for the development of mathematics in primary school, including a measure of adaptive expertise with school mathematics. These include mathematical tasks with non-symbolic quantities, whole numbers, and rational numbers. The participants were 406 primary school students attending the 5th grade

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50

Daugulis, Pēteris, Elfrīda Krastiņa, Anita Sondore, and Vija Vagale. "VARIETY OF ARRANGEMENTS OF NUMERICAL DATA FOR A DEEPER UNDERSTANDING OF MATHEMATICS." SOCIETY. INTEGRATION. EDUCATION. Proceedings of the International Scientific Conference 1 (May 20, 2020): 107. http://dx.doi.org/10.17770/sie2020vol1.5081.

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Effective arranging of numerical data and design of associated computational algorithms are important for any area of mathematics for teaching, learning and research purposes. Usage of various algorithms for the same area makes mathematics teaching goal-oriented and diverse. Matrices and linear-algebraic ideas can be used to make algorithms visual, two dimensional (2D) and easy to use. It may contribute to the planned educational reforms by teaching school and university students deeper mathematical thinking. In this article we give novel data arranging techniques (2D and 3D) for matrix multip

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